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79
Voted
SIGKDD
2000
75views more  SIGKDD 2000»
15 years 1 months ago
Mining Patterns in Long Sequential Data with Noise
Wei Wang 0010, Jiong Yang, Philip S. Yu
102
Voted
SIGKDD
2000
95views more  SIGKDD 2000»
15 years 1 months ago
Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data
Jaideep Srivastava, Robert Cooley, Mukund Deshpand...
SIGKDD
2000
92views more  SIGKDD 2000»
15 years 1 months ago
WEBKDD 2000 - Web Mining for E-Commerce
In this paper, we provide a summary of the WEBKDD 2000 workshop, whose theme was `Web Mining for E-Commerce'. This workshop was held in conjunction with the ACM SIGKDD Intern...
Myra Spiliopoulou, Jaideep Srivastava, Ron Kohavi,...
SIGKDD
2000
112views more  SIGKDD 2000»
15 years 1 months ago
Profiling your Customers using Bayesian Networks
Paola Sebastiani, Marco Ramoni, Alexander Crea
77
Voted
SIGKDD
2000
130views more  SIGKDD 2000»
15 years 1 months ago
KDD-Cup 99: Knowledge Discovery In a Charitable Organization's Donor Database
Saharon Rosset, Aron Inger
SIGKDD
2000
89views more  SIGKDD 2000»
15 years 1 months ago
Measuring Lift Quality in Database Marketing
Gregory Piatetsky-Shapiro, Sam Steingold
77
Voted
SIGKDD
2000
89views more  SIGKDD 2000»
15 years 1 months ago
Winning the KDD99 Classification Cup: Bagged Boosting
Bernhard Pfahringer
SIGKDD
2000
96views more  SIGKDD 2000»
15 years 1 months ago
The MP13 Approach to the KDD'99 Classifier Learning Contest
The MP13 method is best summarized as recognition based on voting decision trees using "pipes" in potential space. Keywords Voting; Decision Tree; Potential Space
Vladimir Miheev, Alexei Vopilov, Ivan Shabalin
SIGKDD
2000
96views more  SIGKDD 2000»
15 years 1 months ago
Phenomenal Data Mining: From Data to Phenomena
Phenomenal data mining finds relations between the data and the phenomena that give rise to data rather than just relations among the data. For example, suppose supermarket cash r...
John McCarthy